15 citations · 27 across the 5 of their papers we have counts for
5 papers
Inference of hidden common driver dynamics by anisotropic self-organizing neural networks
Zsigmond Benkő, Marcell Stippinger, Zoltán Somogyvári
We are introducing a novel approach to infer the underlying dynamics of hidden common drivers, based on analyzing time series data from two driven dynamical systems. The inference…
Detecting Causality in the Frequency Domain with Cross-Mapping Coherence
Zsigmond Benkő, Bálint Varga, Marcell Stippinger +1
Understanding causal relationships within a system is crucial for uncovering its underlying mechanisms. Causal discovery methods, which facilitate the construction of such models f…
Manifold-adaptive dimension estimation revisited
Zsigmond Benkő, Marcell Stippinger, Roberta Rehus +6
Data dimensionality informs us about data complexity and sets limit on the structure of successful signal processing pipelines. In this work we revisit and improve the manifold-ada…
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series
Zsigmond Benkő, Tamás Bábel, Zoltán Somogyvári
Recognition of anomalous events is a challenging but critical task in many scientific and industrial fields, especially when the properties of anomalies are unknown. In this paper,…
Complete Inference of Causal Relations between Dynamical Systems
Zsigmond Benkő, Ádám Zlatniczki, Marcell Stippinger +5
From ancient philosophers to modern economists, biologists, and other researchers, there has been a continuous effort to unveil causal relations. The most formidable challenge lies…